MétaCan
Menu
Back to cohort
Record W2142049317 · doi:10.3138/ptc.2011-25bh

Scores on the Safe Functional Motion Test Are Associated with Prevalent Fractures and Fall History

2012· article· en· W2142049317 on OpenAlexaffvenue
Chris Recknor, Stephanie Grant, Julie C. Recknor, Norma J. MacIntyre

Bibliographic record

VenuePhysiotherapy Canada · 2012
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTest (biology)MedicineMotion (physics)Physical medicine and rehabilitationComputer scienceArtificial intelligenceGeology

Abstract

fetched live from OpenAlex

PURPOSE: The Safe Functional Motion test (SFM) was developed to measure observed body mechanics and functional motion associated with spine load, balance, strength, and flexibility during everyday tasks to profile modifiable risks for osteoporotic fracture. This cross-sectional study evaluated the associations between SFM score and history of vertebral compression fracture (VCF), hip fracture, and injurious falls, all established predictors of future risk. METHOD: An osteoporosis clinic database was queried for adults with an initial SFM score and corresponding data for prevalent VCF and/or hip fracture, femoral neck bone mineral density (fnBMD), and history of injurious fall (n=847). Multiple logistic regressions, adjusted for age, gender, and fnBMD (and injurious falls in the prevalent fracture analyses), were used to determine whether associations exist between SFM score and prevalent VCF, prevalent hip fracture, and history of injurious fall. RESULTS: SFM score was associated with prevalent VCF (odds ratio [OR]=0.89; 95% CI, 0.79-0.99; p=0.036), prevalent hip fracture (OR=0.77; 95% CI, 0.65-0.92; p=0.004), and history of injurious fall (OR=0.80; 95% CI, 0.70-0.93; p=0.003) after adjusting for other important covariates. CONCLUSIONS: Adults with higher SFM scores ("safer motion" during performance of everyday tasks) were less likely to have a history of fracture or injurious fall. Further study is warranted to evaluate the predictive value of this tool.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.279
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2012
Admission routes2
Has abstractyes

Explore more

Same venuePhysiotherapy CanadaSame topicBone health and osteoporosis researchFrench-language works237,207